An impedance detection device for a multi-channel transcranial electrical stimulator

Abstract

The present invention discloses an impedance detection device for a multi-channel transcranial electrical stimulator, which includes a multi-channel electrical stimulation output module, a DAC output module, an ADC acquisition module, an FFT processing module, and an impedance detection and calculation module; the FFT processing module is respectively connected to the ADC acquisition module and the impedance detection and calculation module, and the DAC output module is connected to the multi-channel electrical stimulation output module. The present invention does not require an additional power supply or electrodes, and calculates the impedance corresponding to each electrode only by using the difference between the frequencies of the multi-channel stimulation signals. The core principle of the present invention is that interference will occur between the outputs of the multi-channel current signals in the common cathode circuit, and the real-time impedance situation of the corresponding electrode is judged according to the numerical value of the mutual influence between the signals of the channels.

Description

Technical Field

[0001] The present invention relates to an impedance detection device for a multi-channel transcranial electrical stimulator. Background Art

[0002] Impedance detection is one of the indispensable parts in various transcranial electrical stimulation systems (tDCS, tACS, tRNS). For a voltage output system, the electrode impedance will divide the voltage. The greater the impedance, the smaller the actual stimulation power of the human body, and the less obvious the stimulation effect. For a current output system, first, because the current output is fixed, extra power will be generated when passing through the electrode. If the device is powered by a battery, the overall usage time will be reduced. Second, to ensure a stable current output, the output voltage needs to change at any time according to the overall impedance (electrode and human body). To ensure safety, the output voltage needs to be controlled within a certain range. If the impedance is too large, the overall stimulation signal will be distorted, affecting the stimulation effect. Finally, if the electrode impedance is large, it means poor contact with the human body and a small contact area. When the current passes through, it may burn the skin of the corresponding area. In summary, for a transcranial electrical stimulation system, to ensure a good stimulation effect, impedance monitoring is essential and it should not interfere with normal stimulation experiments.

[0003] The impedance in a transcranial electrical stimulation system generally consists of three parts: electrode impedance, contact impedance, and human impedance. However, generally, impedance detection mainly analyzes the electrode contact impedance because the impedance of the electrode itself is determined by the materials used, and the human impedance is relatively complex and varies among individuals. Although it is not easy to optimize these two, generally, their actual impedance (tens to hundreds of ohms) is much smaller than the contact impedance between the electrode and the human body (hundreds to tens of thousands of ohms). Therefore, the other two are often ignored in the calculation to simplify the calculation.

[0004] The currently commonly used impedance detection methods are mainly divided into DC signal detection and AC signal detection according to different input waveforms. DC signal detection requires inputting a DC signal and then detecting the voltage and current values at both ends of the electrode, and using Ohm's law to calculate the overall impedance. To minimize interference with the stimulation experiment, the input signal is mainly a short-term pulse signal or a square wave signal. The advantages are simple structure and low cost, but it is usually only applicable to single-channel impedance detection. For multi-channel electrical stimulation output, the current between different channels will cause crosstalk, and the simple impedance detection result will become unreliable. The currently commonly used impedance detection waveform is an AC signal, mainly because the high-frequency AC signal has less impact on the brain compared to the DC signal, and the output is not easily interfered by the electroencephalogram signal frequency (a few Hz to several hundred Hz).

[0005] US 9339642 B1, "System and method for conducting multi - electrode electrical stimulation", discloses a stimulation and monitoring method applicable to multi - electrode experiments. Its structure is as shown in Figure 1 shown. The controller is responsible for configuring the parameters of each module. The output source is divided into a first stimulation source and a second stimulation source. The first stimulation source is the main output and is responsible for generating the stimulation signals required for the experiment. The second stimulation source outputs a signal different from the first source for impedance detection. For example, in a transcranial direct current stimulation experiment (tDCS), the first stimulation source generates the required DC signal for the experiment, and the second stimulation source outputs a high - frequency low - amplitude sine signal. While not affecting the effect of the DC stimulation experiment, the electrode impedance is calculated by measuring the AC signal. The monitor is responsible for collecting the signals of each electrode and calculating the impedance. This patent application only proposes that a multi - electrode stimulation method can be achieved through two stimulation sources and one monitor, and specifically describes how to build the entire system by changing the electrode connection method, without in - depth discussion of the specific impedance detection algorithm.

[0006] "Methods for Specific Electrode Resistance Measurement During Transcranial Direct Current Stimulation", a method for specific electrode impedance detection during tDCS stimulation. This paper proposes a method for measuring the impedance of stimulation electrodes by adding an additional electrode or an additional power source. Multi - channel direct current stimulation can calculate the impedance of the anode and cathode electrodes by adding an additional reference electrode to measure the brain voltage increase equation, or by outputting a high - frequency current signal with a DC bias as the experimental signal by the current source. Separate the DC and AC signals, use the DC as the main experimental signal, and use the AC signal as the auxiliary signal to establish multiple equations to calculate the real - time impedance of each electrode. This method is only limited to tDCS experiments and is not applicable to other transcranial electrical stimulations.

[0007] CN201810566020.3, "An impedance detection system in transcranial electrical stimulation", provides an impedance detection method applicable to various transcranial electrical stimulations. It mainly includes a DA module, an MCU unit, an AD sampling module, and an AD sampling module. The MCU controls the output signal parameters to drive the DA to generate an analog impedance detection signal. After output, peak detection and related control are performed. Finally, the AD collects the corresponding signal and calibrates the data by the least - squares method, and returns the data to the MCU to perform real - time control of the entire process. The impedance detection system designed in this application only adds peak detection and AD calibration to the existing method of measuring impedance by outputting a detection signal. The purpose is to achieve relatively accurate impedance measurement with a low - cost method, without innovating on the specific algorithm and without involving multi - channel impedance detection.

[0008] Currently, the commonly used impedance detection methods require providing additional signal inputs or independent reference electrodes for monitoring impedance. The entire system may generate a large amount of additional power. At the same time, due to the complex impedance conditions of the human body and electrodes in actual situations, the impedance results obtained using different test signals (DC, square wave, sine waves of different frequencies) vary greatly. Moreover, in order not to interfere with the stimulation experiment, the test signal often differs significantly from the stimulation signal parameters and cannot well reflect the impedance changes before or during the experiment. Summary of the Invention

[0009] The object of the present invention is to overcome the deficiencies of the prior art and provide an impedance detection device for a multi-channel transcranial electrical stimulator that calculates the impedance corresponding to each electrode using only the differences between the frequencies of multi-channel stimulation signals without the need for an additional power source or electrodes.

[0010] The object of the present invention is achieved through the following technical solutions: An impedance detection device for a multi-channel transcranial electrical stimulator includes a multi-channel electrical stimulation output module, a DAC output module, an ADC acquisition module, an FFT processing module, and an impedance detection calculation module; the FFT processing module is respectively connected to the ADC acquisition module and the impedance detection calculation module, and the DAC output module is connected to the multi-channel electrical stimulation output module;

[0011] The multi-channel electrical stimulation output module is used to provide multi-channel digital signals with different frequencies required for transcranial electrical stimulation and send them to the DAC output module;

[0012] The DAC processing module is used to convert the digital signals transmitted by the multi-channel electrical stimulation output module into current signals to generate experimental stimulation signals;

[0013] The ADC acquisition module is used to convert the continuous analog signals collected by the electrodes of each channel into digital signals and transmit them to the FFT processing module;

[0014] The FFT processing module converts the digital signals collected by the ADC acquisition module into frequency-domain signals and separates the voltage components of different frequencies at each electrode point;

[0015] The impedance detection calculation module receives the voltage values of each frequency after FFT processing and calculates the impedance values of each electrode point according to the impedance detection formula.

[0016] Further, the specific calculation method for the impedance value of each electrode point is: Let R 1 and R 3 represent the contact resistances of the two electrodes of the first stimulation channel, R 2 and R 4 represent the contact resistances of the two electrodes of the second stimulation channel, Rt Represents the simplified impedance of the human body, R ef1 and R ef2 are fixed reference resistors;

[0017] R 1 、R 3 、R ef1 are connected in series, and R 2 、R 4 、R ef2 are connected in series. The input frequency voltage components of the two stimulation channels are S 1 and S 2 , and the currents are I 1 、I 2 ; R t is connected in parallel between the output terminals of R 1 and R 2 ;

[0018] U 1 、U 2 、U 3 、U 4 respectively represent the voltages at the four electrodes, subdividing the voltage components of two different frequencies of the first stimulation channel and the second stimulation channel. U 1 is divided into U 1S1 and U 1S2 , respectively representing the frequency voltage component of S 1 and the frequency component of S 2 . The same applies to the other electrodes; U t1 and U t2 represent the voltage values at the brain of the first stimulation channel and the second stimulation channel; for a single voltage U t1 is also subdivided into the frequency voltage component U 1 of S t1S1 and the frequency component U 2 of S t1S2 . Similarly, U t2 is divided into U t2S1 and U t2S2 ; U t1 and U t2 cannot be directly obtained, but according to the current crosstalk principle, the values U 1 and U 2 at which the rising values disturbed by the other channel at U 1S2 and U 2S1 are approximately regarded as the values U 2 and U 1 at the brain of S t2S2 and U t1S1 . Since then, the estimated voltages at both ends of R 1 and R 2 with respect to the frequencies of their own channels are known, and their impedance values can be approximately calculated; similarly, R 3 and R4 With the known voltage at both ends, use R ef to estimate the return channel current value; thus, according to the above description, the estimation formulas for the contact impedance of each electrode are as follows:

[0019] R 1 =(U 1S1 -U t2S1 ) / I 1

[0020] R 2 =(U 2S2 -U t1S2 ) / I 2

[0021]

[0022]

[0023] The beneficial effects of the present invention are as follows: The present invention provides an impedance detection device for a multi-channel transcranial stimulation device. Its main feature is that no additional power supply or electrodes are required, and the impedance corresponding to each electrode is calculated only using the difference between the frequencies of multi-channel stimulation signals. The core principle of the present invention is to utilize the interference generated between the multi-channel current signal outputs in a common cathode circuit, and judge the real-time impedance situation of the corresponding electrode according to the numerical value of the mutual influence between the signals of different channels. In a common cathode system, when multiple channels need to simultaneously send fixed current signals, the voltage at both ends of the load increases. To maintain the same current output for each channel, the voltage at both ends of the electrode will rise to a certain extent. This interference also follows Ohm's law. The changed value of the interference between channels is linearly positively correlated with the magnitude of the electrode impedance. Using this principle, as long as the frequencies between the stimulation channels are different to separate the frequency information of other channels on each electrode, the electrode impedance can be calculated. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a schematic structural diagram of a multi-electrode electrical stimulation conduction system in 《System and method for conducting multi-electrode electrical stimulation》;

[0025] Figure 2 is a schematic structural diagram of the impedance detection device of the present invention;

[0026] Figure 3 is a schematic diagram of single-channel impedance detection;

[0027] Figure 4 is a schematic diagram of a two-channel three-electrode (single ground terminal);

[0028] Figure 5It is a schematic diagram of a dual-channel four-electrode connection;

[0029] Figure 6 It is a schematic diagram of an improved dual-channel four-electrode connection;

[0030] Figure 7 It is a schematic diagram of impedance calculation of the present invention. Specific embodiments

[0031] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0032] As Figure 2 shown, an impedance detection device for a multi-channel transcranial electrical stimulator of the present invention includes a multi-channel electrical stimulation output module, a DAC output module, an ADC acquisition module, an FFT processing module, and an impedance detection and calculation module; the FFT processing module is respectively connected to the ADC acquisition module and the impedance detection and calculation module, and the DAC output module is connected to the multi-channel electrical stimulation output module;

[0033] The multi-channel electrical stimulation output module is used to provide multi-channel digital signals with different frequencies required for transcranial electrical stimulation and send them to the DAC output module; this module is relatively flexible and can be implemented by any circuit. To maintain consistency with subsequent modules, it is mainly implemented by the same digital processing unit in this article. Before the experiment starts, each channel can send short-time electrical signals to calculate the impedance and display the impedance data of each electrode to help the experimenter adjust the poorly contacted electrodes in time; during the experiment, it can continuously output long-time multi-channel stimulation, and this stimulation is simultaneously collected for calculating the real-time impedance situation. If there is an electrode abnormality, it will be displayed in real time on the interface, and at this time, the experiment needs to be interrupted to adjust the electrodes.

[0034] The DAC processing module is used to convert the digital signals transmitted from the multi-channel electrical stimulation output module into current signals to generate experimental stimulation signals;

[0035] The ADC acquisition module is used to convert the continuous analog signals collected by the electrodes of each channel into digital signals and transmit them to the FFT processing module; this module is a necessary analog-to-digital conversion module. The present invention uses digital devices as the core processing module, which can only process digital signals. Therefore, the continuous analog signals collected at each set point need to be converted into digital signals by the ADC and transmitted to the device for subsequent processing.

[0036] The FFT processing module converts the digital signals collected by the ADC acquisition module into frequency-domain signals and separates the voltage components of different frequencies at each electrode point. In the present invention, the same digital calculation unit is also used. First, the time-domain signal data at each electrode is collected by the ADC and then transmitted into the device. The FFT is used to convert the digital signals collected by the ADC acquisition module into frequency-domain signals. Then, the peak values of the output frequency numerical points in the frequency-domain signals of each point are extracted. Since there are problems such as spectrum leakage in the FFT processing, which may cause unstable output values, but the time-domain amplitude change of the signals at the same frequency is proportional to the frequency-domain amplitude. By using this relationship, the amplitude signals of the same output frequency under the impedance data of 1KΩ are collected in advance, and the collected data is normalized to obtain the voltage amplitude components of different frequencies at each electrode point. Finally, the impedance values of each electrode point are calculated according to the impedance detection formula.

[0037] The impedance detection and calculation module receives the voltage values of each frequency after FFT processing and calculates the impedance values of each electrode point according to the impedance detection formula.

[0038] The impedance calculation principle of the present invention is as follows: The impedance detection principle adopted in this article is to add another distinguishable variable to the original stimulation system for auxiliary detection. The original stimulation is called the first stimulation source, and the auxiliary stimulation is called the second stimulation source. In addition, a monitor is required for the acquisition and processing of the corresponding points. The scheme is the same as that in 《System and method for conducting multi-electrode electrical stimulation》, as Figure 1 shown. The embodied impedance detection is as Figure 3 shown. Taking single-channel DC stimulation as an example, R 1 、R 2 、R 3 、R 4 represent the electrode impedance, and R t represents the simplified human body impedance (the actual situation is much more complicated than this. For the convenience of explaining the principle, a simplified diagram is used). I 1 and I 2 are the set current values. The DC signal on the left is the main stimulation signal as the first stimulation source, outputting a DC signal of less than 2mA; the signal on the right is the auxiliary calculation signal as the second stimulation. It is necessary to distinguish the two signal sources from the overall stimulation while not affecting the DC stimulation effect. Therefore, a low-amplitude high-frequency alternating current stimulation can be adopted (1. The human body is insensitive to low-amplitude and low-frequency stimulation. 2. The use of alternating current output can effectively distinguish it from the DC signal of the first current source for subsequent impedance calculation); the source monitor is replaced by a voltmeter, mainly collecting the output voltage across the first stimulation source. The known information in the figure is the set output I 1With I 2 , and the voltage U across the first current source collected, which contains two kinds of voltage information: the DC bias information of the first current source, and the frequency and amplitude information of the AC signal corresponding to the second current source. The specific calculation is as follows:

[0039] It is known that the output is a fixed current I 1 . If there is no AC signal I 2 , then the voltage obtained by the voltage monitor is:

[0040] U = I 1 ×(R 1 + R 2 + R t ) (1)

[0041] At this time, if I 2 is added, the current flowing through R t is I 1 + I 2 , then the voltage across R t is:

[0042] (U 1 - U 2 ) = (I 1 + I 2 )×R t (2)

[0043] U 2 can be easily obtained as:

[0044] U 2 = I 1 R 2 + I 2 R 4 (3)

[0045] Then, from equations (2) and (3), the value of U 1 can be calculated as:

[0046] U 1 = (I 1 R 2 + I 2 R 4 ) + (I 1 + I 2 )R t (4)

[0047] The voltage at the right end of R 1 is known, and the current flowing through R 1 is known. Then, the overall output voltage at the left end can be deduced. Let U′ represent the voltage obtained after the first and second current sources are started simultaneously, and this voltage is equal to the voltage value at the left end of R 1 . Then U′ can be expressed as:

[0048] U′ = (I 1 R 2 + I 2 R 4 ) + (I 1 + I 2 )R t + I 1 R 1 (5)

[0049] After simplification, we get:

[0050] U′ = I 1 (R 1 + R 2 + R t ) + I 2 (R 4 + R t ) (6)

[0051] Comparing the acquisition voltage formula (1) before the start of the second signal source and the voltage formula (6) after the start, it can be seen that when the second output source starts, the first output source needs an additional voltage input to maintain the output current, and this voltage input is determined by the output current of the second current source and one of the contact impedances. This phenomenon not only shows that different channels will affect each other and generate interference when multiple channels are connected simultaneously, but also can use this phenomenon to calculate the parameters we need. The core of the above impedance detection is: being able to identify the voltage contributions of different channel currents to some devices in the overall circuit, and then establishing equations based on these data to calculate the impedance. And current signals can be identified by FFT as long as their frequencies are different. For this article, as long as the multi-channel stimulation frequencies are different, impedance detection can be performed on them, which perfectly meets the requirements of this calculation method. So the following is the application in a specific experimental circuit.

[0052] Figure 4 For the case of two channels and three electrodes (the actual situation should be two channels and four electrodes, but the FPGA chip used is at the common equipotential point or common cathode, and without using other methods, it is impossible to distinguish the electrode impedance situation connected to the equipotential point, so it is temporarily reduced to the same resistance for discussion). The basic parameter settings are Figure 3 basically the same. Considering the situation where the impedance between electrodes is different in the actual situation, R 1 , R 2 , R 3 represent the electrode impedances as the parameters to be calculated, and R t1 , R t2 , R t3 , R t4 represent the simplified human body impedances between electrodes. The specific calculation process is as follows:

[0053] First, the voltage of current source S can be obtained from the figure 1 is expressed as:

[0054]

[0055] This equation can be simplified. Since the contact resistance of the electrode is as high as several thousand ohms, which is much greater than the human impedance of several hundred ohms, the human resistance in Equation (7) can be removed and approximated to obtain:

[0056] U 1 = I 1 (R 1 + R 3 ) + I 2 R 3 (8)

[0057] Similarly, the voltage value across the two ends when only considering S 2 is:

[0058] U 2 = I 2 (R 2 + R 3 ) + I 1 R 3 (9)

[0059] U 1 and U 2 are the overall output voltages of the current source. Since the voltages between channels affect each other, each channel output should have two voltage components with different frequencies according to the current frequency. For example, U 1 can be divided into its own voltage frequency component U1 S1 and the voltage U1 S2 affected and changed by U1 S2 . U1 S2 has the same value as that obtained by collecting and calculating U 1 and U t1 (because its meaning is that S 1 increases the voltage value across U t1 to match the output current). Similarly, U 2 can be divided into U2 S1 and U2 S2 .

[0060] According to the previous discussion, after the current source S 2 is turned on, the voltage across S 1 will be affected by it. If the value of U 1 affected and changed by S 2 can be extracted, an additional calculation formula can be listed. Since the output frequencies of current sources S 1 and S 2 are different, fast Fourier transform is used in this paper to extract the relevant voltage changes and only consider S2 In the case of S 1 is equivalent to an open circuit, and U 1 the voltage of S at U can be collected through the electrode: t1 at U with respect to S 2 is:

[0061]

[0062] The contact resistance R 3 is much greater than the human body impedance, so the formula can also be simplified:

[0063] U2 S1 = I 2 R 3 (11)

[0064] U1 S2 represents the amplitude of the frequency voltage component of S extracted from the time-domain voltage collected by U through FFT transformation. Similarly, for U 1 the voltage of S can be obtained: 2 with respect to S 2 at the frequency of S 1 is:

[0065] U1 S2 = I 1 R 3 (12)

[0066] Therefore, in the case of only considering a single frequency of S 1 or S 2 , the actual output voltage of an electrode, that is, the brain voltage U 1 and U 2 can be approximately obtained by separating the corresponding frequencies. (Approximately equal), the equipotential electrode resistance R t1 or U t2 can be calculated, and according to formula (8), the output electrode resistance can be calculated as: 3 R

[0067] = (U1 1 - U2 S2 ) / I S1 (13) 1 Similarly, R

[0068] can be calculated: 2 R

[0069] = (v2 2 - U1 S2 ) / I S2 (14) 1 (14)

[0070] Figure 5Schematic diagram of dual-channel four-electrode connection under actual conditions, with parameter settings the same as before. Let R 1 and R 3 represent the contact resistances of the two electrodes in the first stimulation channel, R 2 and R 4 represent the contact resistances of the two electrodes in the second stimulation channel, R t represents the simplified human impedance, R ef1 and R ef2 are fixed reference resistors; R 1 , R 3 , R ef1 are in series, R 2 , R 4 , R ef2 are in series, and the input frequency voltage components of the two stimulation channels are S 1 and S 2 , and the currents are I 1 , I 2 ; R t is connected in parallel between the output terminals of R 1 and R 2 ; This connection method is the same as Figure 4 in the case of expanding the equipotential terminal. This connection method cannot separate R 3 , R 4 by calculation. Therefore, other methods need to be introduced to assist in the calculation. The improved connection schematic diagram is as shown in Figure 6 . Fixed reference resistors R 3 , R 4 are added, and the current values I ef1 , I ef2 passing through this channel are calculated by collecting the voltages across the fixed reference resistors. The two resistance values are separated by substituting them into subsequent calculations (where 3 , I 4 For the convenience of subsequent calculations, the human impedance is simplified because the human impedance is much smaller than the electrode contact impedance. The series human impedance in the figure is ignored or understood as incorporated into the contact impedance calculation value). Figure 6 ).

[0071] U 1 , U 2 , U 3 , U 4 represent the voltages at the four electrodes respectively, subdividing the voltage components of the two different frequencies in the first stimulation channel and the second stimulation channel. U 1 is divided into U 1S1 and U 1S2 , representing the frequency voltage component of S 1 and the frequency component of S 2 respectively. The same applies to the other electrodes, as shown in Figure 7 ; U t1 and Ut2 Represents the voltage values of the first and second stimulation channels at the brain; for a single voltage U t1 Is also subdivided into S 1 Frequency voltage component U t1S1 And S 2 Frequency component U t1S2 , Similarly, U t2 Is divided into U t2S1 And U t2S2 ; U t1 And U t2 Cannot be directly obtained, but according to the current crosstalk principle, the rising values U 1 And U 2 At are interfered by the other channel and are approximately regarded as S 1S2 And U 2S1 At the values U 2 And S 1 At the brain; since then, the estimated voltages at both ends of R t2S2 And U t1S1 Are known about the frequencies of their own channels, and their impedance values can be approximately calculated; similarly, the voltages at both ends of R 1 And R 2 Are known, and the return channel current value is estimated using R 3 And R 4 ; the basic calculation method is the same as before, except that a fixed impedance is introduced to calculate the current passing through R ef , R 3 , R 4 And estimate the impedance value by estimating the voltages at both ends.

[0072] Obtain the specific calculation method of impedance in the actual situation:

[0073] R 1 =(U 1S1 -U t2S1 ) / I 1

[0074] R 2 =(U 2S2 -U t1S2 ) / I 2

[0075]

[0076]

[0077] The multi-channel algorithm decomposes the multi-channel into multiple two-channels. As long as any one channel is jointly calculated with other channels with different output frequencies, the impedance sizes of each electrode of this channel can be obtained through the calculation method of the two-channel.

[0078] So far, the input and output electrodes of the dual-channel electrical stimulation can estimate the impedance values, and the error is mainly determined by the human impedance ignored during the calculation. When the electrode contact impedance is large and cannot meet the experimental requirements, the human impedance is much smaller than the contact impedance, and the error can be ignored. When the contact impedance is low, the error is larger, but at this time the overall impedance no longer affects the output of the experimental stimulation signal. The purpose of impedance detection in the transcranial electrical stimulation system is to ensure the correct output of the stimulation waveform rather than accurately measuring the impedance value. The impedance detection algorithm proposed by the present invention fully meets various experimental requirements.

[0079] In addition to the above-mentioned dual-channel stimulation experiment, the present invention can expand the number of stimulation channels without making too many changes to the algorithm. As long as there are output signals with different frequencies during multi-channel stimulation, the input and output electrode impedances of each channel can be calculated one by one using the dual-channel impedance detection algorithm.

[0080] Those of ordinary skill in the art will realize that the embodiments described herein are for helping the reader understand the principles of the present invention, and it should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not depart from the essence of the present invention based on the technical revelations disclosed in the present invention, and these deformations and combinations are still within the protection scope of the present invention.

Claims

1. An impedance detection device for a multi-channel transcranial electrical stimulator, characterized in that, it includes a multi-channel electrical stimulation output module, a DAC output module, an ADC acquisition module, an FFT processing module, and an impedance detection calculation module; the FFT processing module is respectively connected to the ADC acquisition module and the impedance detection calculation module, and the DAC output module is connected to the multi-channel electrical stimulation output module; The multi-channel electrical stimulation output module is used to provide multi-channel digital signals with different frequencies required for transcranial electrical stimulation and send them to the DAC output module; The DAC processing module is used to convert the digital signals transmitted by the multi-channel electrical stimulation output module into current signals to generate experimental stimulation signals; The ADC acquisition module is used to convert the continuous analog signals collected by the electrodes of each channel into digital signals and transmit them to the FFT processing module; The FFT processing module is used to separate the voltage components with different frequencies at each electrode point; The impedance detection calculation module receives the voltage values with different frequencies at each electrode point after FFT processing, and calculates the impedance values of each electrode point according to the impedance detection formula; The specific calculation method for the impedance value of each electrode point is as follows: Let R 1 and R 3 represent the contact resistances of the two electrodes of the first stimulation channel, R 2 and R 4 represent the contact resistances of the two electrodes of the second stimulation channel, R t represents the simplified impedance of the human body, R ef1 and R ef2 are fixed reference resistors; R 1 、R 3 、R ef1 are connected in series. R 2 、R 4 、R ef2 are connected in series. The input frequency voltage components of the two stimulation channels are S 1 and S 2 respectively, and the currents are I 1 、I 2 respectively; R t is connected in parallel between the output terminals of R 1 and R 2 . U 1 , U 2 , U 3 , U 4 Represents the voltage at the four electrodes, subdividing the voltage components of the first stimulation channel and the second stimulation channel with two different frequencies, U 1 Divided into U 1S1 with U 1S2 , representing S 1 Frequency voltage component and S 2 Frequency component, the same applies to other electrodes; U t1 with U t2 Represents the voltage value of the first stimulation channel and the second stimulation channel at the brain; for a single voltage U t1 Also subdivided into S 1 Frequency voltage component U t1S1 With S 2 Frequency component U t1S2 , similarly U t2 Divided into U t2S1 with U t2S2 ; According to the current crosstalk principle, U 1 with U 2 The value U at which the channel is disturbed by the other party 1S2 with U 2S1 Approximately regarded as S 2 With S 1 The value U at the brain t2S2 with U t1S1 , the contact impedance estimation formula of each electrode is as follows: R 1 = (U 1S1 - U t2S1 ) / I 1 R 2 = (U 2S2 - U t1S2 ) / I 2 The multi-channel algorithm decomposes the multi-channel into multiple two-channels. As long as any one channel is combined with other channels with different output frequencies, the impedance magnitudes of the electrodes of this channel can be obtained through the calculation method of the two-channel.

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